tf.compat.v1.data.experimental.Counter
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Creates a Dataset
that counts from start
in steps of size step
.
tf.compat.v1.data.experimental.Counter(
start=0, step=1, dtype=tf.dtypes.int64
)
Unlike tf.data.Dataset.range
which will stop at some ending number,
Counter
will produce elements indefinitely.
dataset = tf.data.experimental.Counter().take(5)
list(dataset.as_numpy_iterator())
[0, 1, 2, 3, 4]
dataset.element_spec
TensorSpec(shape=(), dtype=tf.int64, name=None)
dataset = tf.data.experimental.Counter(dtype=tf.int32)
dataset.element_spec
TensorSpec(shape=(), dtype=tf.int32, name=None)
dataset = tf.data.experimental.Counter(start=2).take(5)
list(dataset.as_numpy_iterator())
[2, 3, 4, 5, 6]
dataset = tf.data.experimental.Counter(start=2, step=5).take(5)
list(dataset.as_numpy_iterator())
[2, 7, 12, 17, 22]
dataset = tf.data.experimental.Counter(start=10, step=-1).take(5)
list(dataset.as_numpy_iterator())
[10, 9, 8, 7, 6]
Args |
start
|
(Optional.) The starting value for the counter. Defaults to 0.
|
step
|
(Optional.) The step size for the counter. Defaults to 1.
|
dtype
|
(Optional.) The data type for counter elements. Defaults to
tf.int64 .
|
Returns |
A Dataset of scalar dtype elements.
|
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Last updated 2021-08-16 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2021-08-16 UTC."],[],[]]